import math import multiprocessing import argparse from random import shuffle import torch.multiprocessing as mp import torch from glob import glob from tqdm import tqdm import utils from data_conf import data_root from module.cnhubert import get_model, get_content import logging logging.getLogger("numba").setLevel(logging.WARNING) import librosa def process_one(file_path, model): # file_path16k = file_path.replace('genshin_data', 'genshin_data16k') ssl_path = file_path.replace(".wav", ".ssl.pt").replace(".mp3", ".ssl.pt") ssl_content = get_content(model, file_path) assert not torch.isnan(ssl_content).any(), f"NaN in {file_path}" torch.save(ssl_content.half().cpu(), ssl_path) def process_batch(filenames): print("Loading content model...") rank = mp.current_process()._identity rank = rank[0] if len(rank) > 0 else 0 gpu_id = rank % torch.cuda.device_count() device = torch.device(f"cuda:{gpu_id}") ssl_model = get_model() ssl_model = ssl_model.to(device) ssl_model.eval() print("Loaded content model.") for filename in tqdm(filenames): try: process_one(filename, ssl_model) except Exception as e: print(f"Error processing {filename}: {e}") if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( "--config", type=str, default="configs/vits.json", help="path to config" ) args = parser.parse_args() filenames = glob(f"{data_root}/**/*.wav", recursive=True) # [:10] filenames += glob(f"{data_root}/**/*.mp3", recursive=True) # [:10] hps = utils.get_hparams_from_file(args.config) shuffle(filenames) multiprocessing.set_start_method("spawn", force=True) num_processes = 1 chunk_size = int(math.ceil(len(filenames) / num_processes)) chunks = [ filenames[i : i + chunk_size] for i in range(0, len(filenames), chunk_size) ] print([len(c) for c in chunks]) processes = [ multiprocessing.Process(target=process_batch, args=(chunk, )) for chunk in chunks ] for p in processes: p.start()